SafeSpace is a native Android application developed entirely in Kotlin to help users with stress detection and management. This project incorporates machine and deep learning models include emotion detection using images, recommendations system using sentiment analysis and stress detection using sensors which were developed as a part of this project. This project was created as part of a summer internship at Thapar Institute of Engineering and Technology (TIET).
- Feature
- Deployments
- Technologies Used
- Contributors
- Stress Management: Provides personalized tips and resources for managing stress effectively.
- Android App: A modern Android native app built in kotlin. (https://github.com/varunkumar2004/SafeSpace-Android)
- Image Detection: Stress detection using CNN + ELM model. (https://github.com/varunkumar2004/ELM-Image-Model-ELC-2024)
- IOT: Stress Detection System with MAX30100 and MLX90614 Sensors. (https://github.com/gupta-kritika/SafeSpace_IoT.git)
- Nlp based recommendations: Includes guided recommendations after analysing sentiment of the user when chatting with the bot purposely made for this project.
- Real-Time Monitoring: Tracks stress levels in real-time using connected devices (if applicable).
Deployments -> https://github.com/varunkumar2004/SafeSpace-ELC-Deployments.git
- Kotlin: The primary programming language used for developing the app's logic.
- Android Jetpack: Provides architecture components and tools for building a robust and efficient user interface.
- Deep Learning Models: CNN + ELM Deep learning models for stress detection using images.
- Arduino: Arduino for IOT.
- Firebase: Used for real-time database storage and potential cloud functions (if implemented) to enhance functionality.
- Varun Kumar -> https://github.com/varunkumar2004
- Kritika Gupta -> https://github.com/gupta-kritika
- Prerit Bhagat -> https://github.com/Prerit-Bhagat
- Sukhman Singh -> https://github.com/SUKHMXN
- Jaideep Singh -> http://www.github.com/singhjaideep1098